Data Engineer

Overview

Build, maintain and scale the data pipelines that power a global ecommerce and marketplace platform, ensuring reliability of the data ecosystem during the India business day, within GCP, BigQuery, Snowflake, Airflow and DBT.

What you'll do

• Manage and optimize production data pipelines to ensure timely delivery of high-quality data to the data warehouse.
• Maintain and evolve transformation models using DBT, structuring data for performance and ease of use by analysts.
• Implement and monitor Service Level Objectives (SLOs) and observability alerts in Datadog to proactively detect and resolve pipeline failures.
• Develop and refine workflow orchestration in Airflow, reducing technical debt and improving data processing speed.
• Collaborate across time zones with the Melbourne and New York teams to provide "follow-the-sun" support and ensure global system stability.
• Lead data modeling efforts, transforming raw application and third-party data into well-structured, warehouse-ready assets using Kimball or "one-big-table" paradigms.
• Mentor and elevate the engineering team through rigorous code reviews, documentation standards, and adoption of modern transformation tools such as dbt and SQLMesh.
• Execute migration projects that move legacy data structures into the modern cloud architecture.
• Implement and maintain systems for data governance, focusing on automated testing, data quality, consistency and privacy compliance across all global pipelines.

What you'll need

• 5+ years of experience building and maintaining production-grade data pipelines in a cloud-native environment (GCP preferred, or AWS).
• Deep proficiency in Python and SQL, with a strong background in data modeling and API integration.
• Hands-on experience with BigQuery/Snowflake, DBT, and Airflow (or similar orchestration tools such as Dagster or Prefect).
• Understanding of how to process large-scale datasets efficiently using tools like Spark or BigQuery.
• Ability to work effectively in a distributed team, clearly documenting technical changes and participating in global handover processes.
• Reliability-first mindset, taking pride in high uptime and the accuracy of the data delivered.
• View data as a product and strive to make it accessible and understandable for stakeholders across the business.
• Thrive in a fast-paced environment and be comfortable shifting between deep-focus development and urgent troubleshooting.
• Stay curious about emerging data technologies and look for ways to automate manual processes.
• Work independently, lead complex projects, work through ambiguity, and build repeatable engineering patterns.

Details

• Location: Gurugram, Haryana, India.
• Operates during the India business day, with follow-the-sun collaboration with Melbourne and New York teams.